Development of a Voice-Input Voice-Output Communication Aid (VIVOCA) for People with Severe Dysarthria

  • Mark S. Hawley
  • Pam Enderby
  • Phil Green
  • Stuart Cunningham
  • Rebecca Palmer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4061)


This paper describes an approach to the development of a voice-input voice-output communication aid (VIVOCA) for people with disordered or unintelligible speech, initially concentrating on people with moderate to severe dysarthria. The VIVOCA is intended to recognize and interpret an individual’s disordered speech and speak out an equivalent message in clear synthesized speech. User consultation suggests that such a device would be acceptable and would be useful in communication situations where speed and intelligibility are crucial. Speech recognition techniques will build on previously successful development of speech-based home control interfaces, and various methods for speech ‘translation’ are being evaluated.


Assistive Technology Automatic Speech Recognition Large Vocabulary Translation Scheme Speech Technology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Enderby, P., Emerson, L.: Does Speech and Language Therapy Work?, p. 84. Singular Publications (1995)Google Scholar
  2. 2.
    Hawley, M.S., Enderby, P., Green, P., Brownsell, S., Hatzis, A., Parker, M., Carmichael, J., Cunningham, S., O’Neill, P., Palmer, R.: STARDUST; Speech Training And Recognition for Dysarthric Users of Assistive Technology. In: Craddock, G.M., et al. (eds.) Assistive Technology – Shaping the Future, pp. 959–964. IOS Press, Amsterdam (2003)Google Scholar
  3. 3.
    Green, P.D., Carmichael, J., Hatzis, A., Enderby, P.M., Hawley, M., Parker, M.P.: Automatic Speech Recognition with Sparse Training Data for Dysarthric Speakers. In: Proc. European Conference on Speech Technology (Eurospeech), Geneva, pp. 1189–1192 (2003)Google Scholar
  4. 4.
    Holmes, J.N., Holmes, W.: Speech Synthesis and Recognition. Taylor & Francis, Abington (2001)Google Scholar
  5. 5.
    Hatzis, A., Green, P.D., Carmichael, J., Cunningham, S.P., Palmer, R., Parker, M.P., O’Neill, P.: An Integrated Toolkit Deploying Speech Technology for Computer Based Speech Training with Application to Dysarthric Speakers. In: Proc. European Conference on Speech Technology (Eurospeech), Geneva, pp. 2213–2216 (2003)Google Scholar
  6. 6.
    Parker, M., Cunningham, S., Enderby, P., Hawley, M.S., Green, P.: Automatic speech recognition and training for severely dysarthric users of assistive technology – the STARDUST project. Clinical Linguistics and Phonetics 20(2-3), 149–156 (2006)CrossRefGoogle Scholar
  7. 7.
    Hermansky, H., Morgan, N.: RASTA processing of speech. IEEE Trans. Speech & Audio Proc. 2, 587–589 (1994)Google Scholar
  8. 8.
    Cooke, M.P., Green, P.D., Josifovski, L., Vizinho, A.: Robust automatic speech recognition with missing and uncertain acoustic data. Speech Communication 34, 267–285 (2001)MATHCrossRefGoogle Scholar
  9. 9.
    Cross, R.T., Baker, B.R., Klotz, L.V., Badman, A.L.: Semantic compaction in both static and dynamic environments: a new synthesis. In: CSUN conference, Los Angeles (March 1998), Available at

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mark S. Hawley
    • 1
  • Pam Enderby
    • 2
  • Phil Green
    • 3
  • Stuart Cunningham
    • 4
  • Rebecca Palmer
    • 2
  1. 1.Dept. of Medical Physics and Clinical EngineeringBarnsley Hospital NHS Foundation TrustBarnsleyUK
  2. 2.Institute of General Practice and Primary CareUniversity of SheffieldUK
  3. 3.Dept. of Computer ScienceUniversity of SheffieldUK
  4. 4.Dept. of Human Communication ScienceUniversity of SheffieldUK

Personalised recommendations